The following Insight is a featured article from WCG’s 2025 Trends & Insights Report. If you would like to read more insights from this report, please click here.
The adoption of Generative AI (GenAI) by consumers and enterprises has easily exceeded that of the internet, PCs, or mobile devices. In the United States, 40% of adults use GenAI,¹ 65% of organizations provide employees with access to GenAI services,² and 70% of teens are engaging with this technology.³ While these metrics are impressive, true success lies in seamlessly integrating GenAI into daily workflows to unlock its potential and deliver tangible value.
The complexity of clinical trials continues to grow, and GenAI offers promising solutions to address these challenges. From streamlining protocol design to automating patient recruitment, GenAI is already reshaping how trials are conducted. By summarizing large datasets, structuring unstructured content, generating documentation, and personalizing communications, it enables researchers to focus on advancing therapies. At WCG, we’re leveraging GenAI to enhance operational efficiency while maintaining compliance, ensuring that innovation goes hand-in-hand with ethical practices. The real power of GenAI lies in embedding it into workflows in a way that reduces manual burdens and accelerates decision-making.
Just because we can, doesn’t always mean we should — this principle is especially true for GenAI given its ubiquity and relative availability. To identify the optimal uses for GenAI at WCG, we expanded our intake funnels, interviewed key stakeholders from across our enterprise, and conducted rapid pilots to hone in on the opportunities best suited to benefit from this technology. Through this process, we uncovered patterns that allowed us to shift from asking, “Can we use AI for …?” to asking, “How can we scale this to streamline processes, allowing us to focus on higher-value work?”. Most of our use cases were classified into one of three areas: document assistants, language assistants, and tools for automating formulaic or repetitive tasks. This also allowed us to reuse and accelerate both implementation and adoption, maximizing the value of GenAI for our teams.
“Build it, and they will come” — right? Wrong. Despite the recently popular saying, “AI won’t replace your job, but someone using AI will”4, adopting change is challenging, particularly in regulated operational environments. Even with strong leadership buy-in, comprehensive training (a critical yet often underrated component with GenAI), and robust change management support, hidden hurdles often emerge. These include loss aversion, lack of trust, and apprehension about new tools and methods— challenges compounded by the uncertainties surrounding GenAI’s capabilities and limitations.
We’ve found that the more invisible the integration is, the more effective GenAI becomes in our workflows. It smooths adoption by removing barriers to use and also gathers telemetry data to quantify value creation. Whether it’s a plugin to Microsoft Office, a background operation that transforms document information into structured data, or an automated language-processing function within a pre-existing tool, the more native and integrated it is, the easier it is to use. A good example is the simplicity of ChatGPT’s input box interface, which was instrumental in bringing GenAI to the masses.
GenAI serves as an assistant, not a replacement, emphasizing the need for thoughtful review and oversight of its output. Responsibility ultimately lies with the individual who triggers the operation and is provided with the opportunity to update the output – a practice referred to as “human in the loop.” Looking ahead to 2025, ethical and responsible use of AI will be a prominent theme in the headlines, as well as AI governance, which will outline practices the industry needs to operationalize to ensure adherence to data training privacy, regional regulations, transparency in training data, and guardrails for its use. A topic for another day, but in the meantime, let’s not fall asleep at the wheel.
References:
- Pew Research Center, 2024
- Gartner, AI Adoption Trends Report 2024
- Common Sense Media Study, 2024
- Andrew Ng, AI in Practice, 2023
Related Insights:
Ethical Review & AI in Clinical Trials
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